Kiểm tra và cài đặt Maven

Cài đặt bằng lệnh

sudo apt update
sudo apt install maven

Kiểm tra

mvn -version

Nếu cài đặt đúng thì sẽ trả về

Apache Maven 3.6.3
Maven home: /usr/share/maven
Java version: 1.8.0_442, vendor: Private Build, runtime: /usr/lib/jvm/java-8-openjdk-amd64/jre
Default locale: en_US, platform encoding: ANSI_X3.4-1968
OS name: "linux", version: "5.15.167.4-microsoft-standard-wsl2", arch: "amd64", family: "unix"

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Tạo Project bằng Maven

Khởi tạo

mvn archetype:generate -DgroupId=com.example -DartifactId=SparkApp -DarchetypeArtifactId=maven-archetype-quickstart -DarchetypeVersion=1.4 -DinteractiveMode=false
  • Lưu ý: nếu bị lỗi có thể do thiếu quyền ở thư mục gì đó. Hãy thử tạo ở home
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sau đó sẽ được thư mục có cấu trúc như sau
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Config

Thêm vào pom.xml

	<dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-core_2.12</artifactId>
        <version>3.5.3</version>
    </dependency>
    
    <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-sql_2.12</artifactId>
        <version>3.5.3</version>
    </dependency>
    
    <dependency>
	    <groupId>org.apache.spark</groupId>
	    <artifactId>spark-core_2.12</artifactId>
	    <version>3.5.3</version>
	</dependency>

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Config java

<build>
    <plugins>
        <plugin>
            <groupId>org.apache.maven.plugins</groupId>
            <artifactId>maven-compiler-plugin</artifactId>
            <version>3.8.1</version>
            <configuration>
                <source>1.8</source>
                <target>1.8</target>
                <encoding>UTF-8</encoding>
            </configuration>
        </plugin>
    </plugins>
</build>

Full file

<?xml version="1.0" encoding="UTF-8"?>

<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">

  <modelVersion>4.0.0</modelVersion>
  <groupId>com.example</groupId>
  <artifactId>SparkApp</artifactId>
  <version>1.0-SNAPSHOT</version>

  <name>SparkApp</name>

  <!-- FIXME change it to the project's website -->

  <url>http://www.example.com</url>

  <properties>
    <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    <maven.compiler.source>1.7</maven.compiler.source>
    <maven.compiler.target>1.7</maven.compiler.target>
  </properties>

  <dependencies>
    <dependency>
      <groupId>junit</groupId>
      <artifactId>junit</artifactId>
      <version>4.11</version>
      <scope>test</scope>
    </dependency>

  <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-core_2.12</artifactId>
        <version>3.5.3</version>
    </dependency>
    
    <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-sql_2.12</artifactId>
        <version>3.5.3</version>
    </dependency>

  </dependencies>

  <build>
    <pluginManagement><!-- lock down plugins versions to avoid using Maven defaults (may be moved to parent pom) -->
      <plugins>
        <!-- clean lifecycle, see https://maven.apache.org/ref/current/maven-core/lifecycles.html#clean_Lifecycle -->
        <plugin>
          <artifactId>maven-clean-plugin</artifactId>
          <version>3.1.0</version>
        </plugin>
        <!-- default lifecycle, jar packaging: see https://maven.apache.org/ref/current/maven-core/default-bindings.html#Plugin_bindings_for_jar_packaging -->
        <plugin>
          <artifactId>maven-resources-plugin</artifactId>
          <version>3.0.2</version>
        </plugin>
        <plugin>
          <artifactId>maven-compiler-plugin</artifactId>
          <version>3.8.0</version>
        </plugin>

        <plugin>
          <artifactId>maven-surefire-plugin</artifactId>
          <version>2.22.1</version>
        </plugin>

        <plugin>
          <artifactId>maven-jar-plugin</artifactId>
          <version>3.0.2</version>
        </plugin>

        <plugin>
          <artifactId>maven-install-plugin</artifactId>
          <version>2.5.2</version>
        </plugin>

        <plugin>
          <artifactId>maven-deploy-plugin</artifactId>
          <version>2.8.2</version>
        </plugin>

        <!-- site lifecycle, see https://maven.apache.org/ref/current/maven-core/lifecycles.html#site_Lifecycle -->

        <plugin>
          <artifactId>maven-site-plugin</artifactId>
          <version>3.7.1</version>
        </plugin>

        <plugin>
          <artifactId>maven-project-info-reports-plugin</artifactId>
          <version>3.0.0</version>
        </plugin>

  

        <plugin>
            <groupId>org.apache.maven.plugins</groupId>
            <artifactId>maven-compiler-plugin</artifactId>
            <version>3.8.1</version>
            <configuration>
                <source>1.8</source>
                <target>1.8</target>
                <encoding>UTF-8</encoding>
            </configuration>

        </plugin>

      </plugins>

    </pluginManagement>

  </build>

</project>

Word Count

Code và dữ liệu

xin chao cac ban xin chao Hadoop Bid Data minh xin tu gioi thieu minh len la Luu Vinh Tuong

package spark.main;

  

import java.util.Arrays;

import org.apache.spark.SparkConf;

import org.apache.spark.api.java.JavaPairRDD;

import org.apache.spark.api.java.JavaRDD;

import org.apache.spark.api.java.JavaSparkContext;

import scala.Tuple2;

  

public class WordCount {

    public static void main(String[] args) {

         SparkConf conf = new SparkConf()

                .setMaster("local[*]")

                .setAppName("Spark Word Count");

  

        try (JavaSparkContext sc = new JavaSparkContext(conf)) {

            String inputPath = "hdfs://vinhtuong-master:9000/input/input_1.txt";

            String outputPath = "hdfs://vinhtuong-master:9000/output/result";

  

            JavaRDD<String> textFile = sc.textFile(inputPath).cache();

  

            JavaPairRDD<String, Integer> wordCounts = textFile

                    .flatMap(line -> Arrays.asList(line.split("\\s+")).iterator())

                    .mapToPair(word -> new Tuple2<>(word.replaceAll("[^a-zA-Z]", "").toLowerCase(), 1))

                    .reduceByKey(Integer::sum);

  

            wordCounts.coalesce(1).saveAsTextFile(outputPath);

  

            System.out.println("Word Count completed. Output saved to " + outputPath);

        }

    }

}

Đóng gói

mvn clean package

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Sau khi đóng gói, chúng ta sẽ được thư mục target như sau:
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Chạy file

spark-submit --class spark.main.WordCount --master local[*] target/SparkApp-1.0-SNAPSHOT.jar

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Check output

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Spark SQL

Code

name,age,city
Alice,30,New York
Bob,25,Los Angeles
Charlie,35,Chicago
David,40,Houston
Emma,22,San Francisco
Frank,28,Seattle
Grace,33,Boston
Henry,27,Denver

package spark.main;

import org.apache.spark.sql.*;

public class SparkSQLExample {
    public static void main(String[] args) {
        SparkSession spark = SparkSession.builder()
                .appName("Spark SQL Example")
                .master("local[*]")
                .getOrCreate();

            Dataset<Row> df = spark.read()
                .option("header", "true")
                .option("inferSchema", "true")
                .csv("hdfs://vinhtuong-master:9000/input/people.csv");


        System.out.println("Du lieu ban dau:");
        df.show();

        System.out.println("Schema:");
        df.printSchema();

        System.out.println("Chon name va age:");
        df.select("name", "age").show();

        System.out.println("Loc nhung nguoi tren 25 tuoi:");
        df.filter("age > 25").show();

        System.out.println("Nhom theo so tuoi va dem so nguoi:");
        df.groupBy("age").count().show();

        df.write().mode("overwrite").csv("hdfs://vinhtuong-master:9000/output/people");


        spark.stop();
    }
}

Đóng gói

mvn clean package

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Chạy file

spark-submit --class spark.main.SparkSQLExample --master local[*] target/SparkApp-1.0-SNAPSHOT.jar

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Check output

  • Output bên hdfs sẽ không có gì. Vì những thao tác mình không lưu lại (check trên code) mà chỉ show ra màn hình
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  • Nên sẽ check file thực thi ở mục trên
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Phân tích dữ liệu bán lẻ với Spark SQL

Chuẩn bị dữ liệu

Lấy dữ liệu tại đây.
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Có tổng bao nhiêu giao dịch, sản phẩm và khách hàng khác nhau?

Code

package spark.main;

import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.SparkSession;

public class part_1 {
	public static void main(String[] args) {
		SparkSession spark = SparkSession.builder()
				.appName("Part-1")
				.master("local")
				.getOrCreate();
		
		Dataset<Row> data = spark.read()
				.option("inferSchema", true)
				.option("header", true)
				.csv("hdfs://vinhtuong-master:9000/input/retails.csv");
				
		// number of customer distinct
		// except 1 because there are value is null of information customer ID
		long cntCustomers = data.select("CustomerID").distinct().count() - 1; 
		
		// number of product distinct
		long cntProdcts = data.select("StockCode").distinct().count();
		
		// number of invoice distinct
		long cntInvoices = data.select("InvoiceNo").distinct().count();
		
		// print 
		System.out.println("Number of customer distinct: " + cntCustomers); 
		System.out.println("Number of product distinct: " + cntProdcts);
		System.out.println("Number of invoice distinct: " + cntInvoices);
		
	}
}

Đóng gói

mvn clean package

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Chạy file

spark-submit --class spark.main.part_1 target/SparkApp-1.0-SNAPSHOT.jar

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Check output

  • Vì bài này không lưu vào hdfs mà chỉ hiển ra màn hình nên chỉ xem lúc chạy file
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Tỉ lệ khách hàng không có thông tin

Code

package spark.main;

import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.SparkSession;

public class part_2 {
	public static void main(String[] args) {
		SparkSession spark = SparkSession.builder()
				.appName("Part-2")
				.master("local")
				.getOrCreate();
		
		Dataset<Row> data = spark.read()
				.option("inferSchema", true)
				.option("header", true)
				.csv("hdfs://vinhtuong-master:9000/input/retails.csv");
				
		// get number of customer (done part 1)
		long cntCustomers = data.select("CustomerID").count();
		
		// get number of customer no information
		long cntCustomersNoInfor = data.select("CustomerID").filter(data.col("CustomerID").isNull()).count();
		
		double ratio = (double) cntCustomersNoInfor / cntCustomers * 100;
		System.out.printf("Ratio no information: %f \n", ratio);
	}
}

Đóng gói

mvn clean package

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Chạy file

spark-submit --class spark.main.part_2 target/SparkApp-1.0-SNAPSHOT.jar

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Check output

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Tỉ lệ khoảng 29,93 % khách hàng không có thông tin

Đâu là nước có số lượng đơn hàng (Quantity) nhiều thứ 3?

Code

package spark.main;

import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.SparkSession;

public class part_3 {
	public static void main(String[] args) {
		SparkSession spark = SparkSession.builder()
				.appName("Part-2")
				.master("local")
				.getOrCreate();
		
		Dataset<Row> data = spark.read()
				.option("inferSchema", true)
				.option("header", true)
				.csv("hdfs://vinhtuong-master:9000/input/retails.csv");
				
		data.createOrReplaceTempView("data");
		spark.sql("select Country, sum(Quantity) as count from data group by Country order by count desc").show();
	}
}

Đóng gói

mvn clean package

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Chạy file

spark-submit --class spark.main.part_3 target/SparkApp-1.0-SNAPSHOT.jar

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Check output

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output sắp xếp từ cao đến thấp => nhiều thứ 3 là EIRE với count = 142637

Từ nào xuất hiện ít nhất trong phần Description?

Code

package spark.main;

import java.util.ArrayList;
import java.util.Arrays;
import java.util.Iterator;
import java.util.List;

import org.apache.spark.api.java.function.FlatMapFunction;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.RowFactory;
import org.apache.spark.sql.SparkSession;
import org.apache.spark.sql.Encoders;
import org.apache.spark.sql.types.StructType;

public class part_4 {
    public static void main(String[] args) {
        SparkSession spark = SparkSession.builder()
                .appName("Part-4")
                .master("local")
                .getOrCreate();
        
        Dataset<Row> data = spark.read()
                .option("inferSchema", true)
                .option("header", true)
                .csv("hdfs://vinhtuong-master:9000/input/retails.csv");
                
        data.where("Description is not null").flatMap(new FlatMapFunction<Row, Row>() {
            private static final long serialVersionUID = 1L;
            private int cnt = 0;
            
            @Override
            public Iterator<Row> call(Row r) throws Exception {
                List<String> listItem = Arrays.asList(r.getString(2).split(" "));
                
                List<Row> listItemRow = new ArrayList<Row>();
                for (String item : listItem) {
                    listItemRow.add(RowFactory.create(cnt, item, 1));
                    cnt++;
                }
                
                return listItemRow.iterator();
            }
        }, Encoders.row(new StructType()
                .add("number", "integer")
                .add("word", "string")
                .add("lit", "integer")))
        .createOrReplaceTempView("data");
        
        spark.sql("select word, count(lit) as count from data group by word order by count desc").show();
    }
}

Đóng gói

mvn clean package

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Chạy file

spark-submit --class spark.main.part_4 target/SparkApp-1.0-SNAPSHOT.jar

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Check output

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Đổi code thành asc để hiển thị từ thấp đến lớn

spark.sql("select word, count(lit) as count from data group by word order by count asc").show();

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Những từ trong bảng là top những xuất hiện ít nhất trong phần description

Sản phẩm nào bán được số lượng (Quantity) lớn nhất ở United Kingdom?

Code

package spark.main;

import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.SparkSession;

public class part_5 {
    public static void main(String[] args) {
        SparkSession spark = SparkSession.builder()
                .appName("Part-4")
                .master("local")
                .getOrCreate();
        
        Dataset<Row> data = spark.read()
                .option("inferSchema", true)
                .option("header", true)
                .csv("hdfs://vinhtuong-master:9000/input/retails.csv");
                
        data.filter(data.col("Country").equalTo("United Kingdom")).createOrReplaceTempView("data");
		spark.sql("select Description, sum(Quantity) as count from data group by Description order by count desc").show();
    
        }
}

Đóng gói

mvn clean package

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Chạy file

spark-submit --class spark.main.part_5 target/SparkApp-1.0-SNAPSHOT.jar

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Check output

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check tên đầy đủ trong csv là WORLD WAR 2 GLIDERS ASSTD DESIGNS
với số lượng 48326

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